usually include Advanced URL Filtering
Local inline categorization (previously known as inline ML) enables the firewall
dataplane to apply machine learning (ML) on webpages to alert users when phishing
entering your network. Local inline categorization dynamically analyzes and detects
malicious content by evaluating various webpage details using a series of ML models.
Each ML model detects malicious content by evaluating file details, including decoder
fields and patterns, to formulate a high probability classification and verdict, which
is then used as part of your larger web security policy. URLs classified as malicious
are forwarded to PAN-DB for additional analysis and validation. You can specify URL
exceptions to exclude any false-positives that might be encountered. This allows you to
create more granular rules for your profiles to support your specific security needs. To
keep up with the latest changes in the threat landscape, inline ML models are updated
regularly and added via content releases. An active Advanced URL Filtering subscription
is required to configure inline categorization.
You can also enable inline ML-based protection to detect malicious Portable Executable (PE),
ELF and MS Office files, and PowerShell and shell scripts in real-time as part of your
Antivirus profile configuration. For more information, refer to: Advanced Wildfire Inline ML.
Local inline categorization isn't supported on the VM-50 or VM50L virtual appliance.